Jibio

Data warehousing recruiter training

  • Course Overview
  • Overview of the Training Framework Examples 
  • Artificial Intelligence described 
  • Getting Started – Who do we need starting out the project 
    • Business Process Architect \ Business Analyst – Summarized 
      • Responsibilities 
      • Skills 
      • Non-Technical Skills
  • Enterprise Architect – Artificial Intelligence systems 
    • Responsibilities 
    • Skills 
    • Non-Technical Skills 
  • Strategic Goal Definition and a Training Framework Case 
    • Goal Identification 
  • High Level technical components and the relationship to the training framework. 
    • Overview of sample solution
    • Chatbot’s 
    • Vision \ Speech Recognition 
    • Advertising & Brand Suggestion 
    • Data Modeling 
      • Data Science and Machine Learning (ML) 
        • What’s is Data Science and Machine Learning. 
        • Examples of Machine Learning that happen every day 
        • How are we going to use ML?  
  • Identification of how an AI project can be operated 
    • Project phases 
      • Why do we start with the data?
      • Can the AI itself be part of the project team? 
  • Who makes up the project team (General)? 
    • Project manager 
    • Technical leader – AI focused EA 
    • Chief data-warehousing architect – Big Data 
  • Business requirements analyst 
    • Data Scientist 
    • Cloud Engineer (DevOps) 
    • Middleware integrations developer (API Developer) 
    • Front-end tools specialist and developer (Mobile Focused) 
    • Quality assurance specialist 
    • Business Analyst 
    • Product Manager 
    • Technical executive sponsor 
  • The clients view of the candidates 
  • Understanding the client’s needs on a Artificial Intelligence project 
  • Candidate breakdown for each position. 
    • Job Description 
    • How do they provide value to the team? 
    • Sample Resumes / CV 
  • What to look out for 
  • Good versus the bad 
  • Key Terms and phrases 
  • Sample Boolean searches 
  • Wrap up